About Retention
The retention score is a measure of how many of your users are coming back to your application.
Why use it
Users will continue using an application and repeatedly return to it if they find value in it.
A low retention indicates that users might not see value in interacting regularly with an application or struggle to achieve the intended usage. On the other hand, a high Retention Score significantly impacts your business results, leading to a higher return on investment (ROI) for your app.
How is it calculated?
| R score | Average of the Retention Rate and Stickiness |
| Returning users | The metric compares the number of users who returned to the application during the selected period with the users from the previous period. |
| Retention rate | Ratio of returning users to all users (comparing with the previous period). |
| Stickiness | Average daily stickiness in the selected date range in the date picker. Daily stickiness is the ratio of Weekly Active Users to Monthly Active Users on that day (WAU/MAU) |
Funnel "How often your users return?"
Based on you selected time range in the date picker, we take all returning users from this period and look at the behaviour of these returning users from the past to classify them into monthly, weekly or daily group. For this we look at the last 90 days (or since user's first session) and calculate number of sessions, days, weeks and months they returned.
| Monthly Active User | The user was active 2 out of 3 months |
| Weekly Active User | User active 75% of weeks in this period (about 9 out of 12) |
| Daily Active User | A weekly user that’s also active >40% of the days in this period (about 3/7) |
| Multiple times per day | A daily user that has more engaged sessions than days |
The warmup period
Keep in mind, some retention metrics require warmup period:
- Stickiness compares weekly to monthly active users. In the first 2-3 weeks HEART does not know the number of your monthly users, so stickiness will be higher than usual.
- Your Retention rate compares users with the previous period, so if there is no data in this period, retention will appear higher in the beginning.
Limitations
HEART may encounter difficulties in accurately assessing returning users in these scenarios:
- When users switch devices: HEART relies on the browser to determine if a user is returning, either using cookies or through the Browser Extension
- Cookie-related problems: For instance, if a user's browser blocks or restricts cookies, it can hinder the ability of HEART to identify them as returning users accurately. Using the SSO to identify the user is a good way to mitigate the issue.
Best Practices
To get the most value in understanding and improving the Retention numbers, we suggest monitoring the numbers for at least 1 month.
Here are our 3 Tips for a high Retention Score:
1. Understand why
Conduct user research to understand why users are not retaining. How much value do people get from the application? What is the application being used for?
Understand whether there might be roadblocks in using the application. Something might be broken that keeps people from coming back / creates frustration.
2. Improve onboarding
Send users an email to invite them into your application and highlight the values of it.
3. Awareness and promotion
Send a reminder over email or other internal channels.
4. Check for limitations
Check if your system is restricting cookies from the user's browser.
